optimizing UAV-to-Car Communications in 3D Environments Through Dynamic UAV Positioning

Abstract

Unmanned Aerial Vehicles (UAVs) can act as re-lays in areas with limited infrastructure to support car-to-car communications. Prior studies on UAV-to-car communications showed that the irregularity of the terrains has a significant impact on link quality. Thus, in this paper, we propose a positioning technique that relies on Particle Swarm optimization (PSO) to optimize the positioning of a UAV in the vehicular environment by considering the irregularities of the terrains that might hinder Line-of-Sight (LOS) conditions. The proposed technique takes into account the path loss caused by the terrains. Simulation results show that the optimization algorithm allows us to determine the best position for the deployed UAVs throughout time by considering the movement of the cars, and also accounting for adjustments in terms of flight altitude. In particular, the latter is adjusted by considering the position of the cars on the ground and the profile of surrounding terrains to determine potential communications blockages, while respecting international regulations regarding flight altitude restrictions.